Cerebral cortex dose sparing for glioblastoma patients: IMRT versus robust treatment planning

Interval Analysis-Based Optimization: A Robust Model for Intensity-Modulated Radiotherapy (IMRT)

Background: Cancer remains one of the leading causes of mortality worldwide, with radiotherapy playing a crucial role in its treatment. Intensity-modulated radiotherapy (IMRT) enables precise dose delivery to tumors while sparing healthy tissues. However, geometric uncertainties such as patient positioning errors and anatomical deformations can compromise treatment accuracy. Traditional methods use safety margins, which may lead to excessive irradiation of healthy organs or insufficient tumor coverage. Robust optimization techniques, such as minimax approaches, attempt to address these uncertainties but can result in overly conservative treatment plans. This study introduces an interval analysis-based optimization model for IMRT, offering a more flexible approach to uncertainty management. Methods: The proposed model represents geometric uncertainties using interval dose influence matrices and incorporates Bertoluzza's metric to balance tumor coverage and organ-at-risk (OAR) protection. The θ parameter allows controlled robustness modulation. The model was implemented in matRad, an open-source treatment planning system, and evaluated on five prostate cancer cases. Results were compared against traditional Planning Target Volume (PTV) and minimax robust optimization approaches. Results: The interval-based model improved tumor coverage by 5.8% while reducing bladder dose by 4.2% compared to PTV. In contrast, minimax robust optimization improved tumor coverage by 25.8% but increased bladder dose by 23.2%. The interval-based approach provided a better balance between tumor coverage and OAR protection, demonstrating its potential to enhance treatment effectiveness without excessive conservatism. Conclusions: This study presents a novel framework for IMRT planning that improves uncertainty management through interval analysis. By allowing adjustable robustness modulation, the proposed model enables more personalized and clinically adaptable treatment plans. These findings highlight the potential of interval analysis as a powerful tool for optimizing radiotherapy outcomes, balancing treatment efficacy and patient safety.

Volumetric changes in gray matter after radiotherapy detected with longitudinal magnetic resonance imaging in glioma patients

BACKGROUND AND PURPOSE

We evaluated volumetric changes in the gray matter (GM) after radiotherapy (RT) and identified factors that were strongly associated with GM volume reduction.

MATERIALS AND METHODS

A total of 461 magnetic resonance imagings (MRI) from 105 glioma patients treated with postoperative RT was retrospectively analyzed. Study patients' MRIs were collected at five time points: before RT and 1 month, 6 months, 1 year, and 2 years after RT. Using the 'FastSurfer' platform, a deep learning-based neuroimaging pipeline, 73 regions were automatically segmented from longitudinal MRIs and their volumetric changes were calculated. Regions were grouped into 10 functional fields. A multivariable linear mixed-effects model was established to identify the potential predictors of significant volume reduction.

RESULTS

The median age was 50 years (range, 16-86 years). Forty-seven (44.8 %) patients were female and 68 (64.8 %) had glioblastoma. Postoperative RT was delivered at 54-60 Gy with or without concurrent chemotherapy. At 2 years after RT, the median volumetric changes in the overall, ipsilateral, and contralateral GM were -3.5%, -4.5%, and -2.4%, respectively. The functional fields of cognition and execution of movement showed the greatest volume reductions. In the multivariable linear mixed model, female sex (normalized coefficient = -0.14, P < 0.001) and the interaction between age at RT and days after RT (normalized coefficient = -6.48e-6, P < 0.001) were significantly associated with GM reduction. The older patients received RT, the greater volume reduction was seen over time. However, in patients with relatively younger age (e.g., 45, 50, and 60 years for hippocampus, Broca area, and Wernicke area, respectively), the volume was not significantly reduced.

CONCLUSIONS

GM volume reduction was identified after RT that could lead to long-term treatment sequelae. Particularly for susceptible patients, individualized treatment and prevention strategies are needed.

Robust optimization of VMAT for prostate cancer accounting for geometric uncertainty

The aim of this study was to propose optimal robust planning by comparing the robustness with setup error with the robustness of a conventional planning target volume (PTV)‐based plan and to compare the robust plan to the PTV‐based plan for the target and organ at risk (OAR). Data from 13 patients with intermediate‐to‐high‐risk localized prostate cancer who did not have T3b disease were analyzed. The dose distribution under multiple setup error scenarios was assessed using a conventional PTV‐based plan. The clinical target volume (CTV) and OAR dose in moving coordinates were used for the dose constraint with the robust plan. The hybrid robust plan added the dose constraint of the PTV‐rectum to the static coordinate system. When the isocenter was shifted by 10 mm in the superior–inferior direction and 8 mm in the right‐left and anterior directions, the doses to the CTV, bladder, and rectum of the PTV‐based plan, robust plan, and hybrid robust plan were compared. For the CTV D_99% in the PTV‐based plan and hybrid robust plan, over 95% of the prescribed dose was secured in all directions, except in the inferior direction. There was no significant difference between the PTV‐based plan and the hybrid robust plan for rectum V_70Gy, V_60Gy, and V_40Gy. This study proposed an optimization method for patients with prostate cancer. When the setup error occurred within the PTV margin, the dose robustness of the CTV for the hybrid robust plan was higher than that of the PTV‐based plan, while maintaining the equivalent OAR dose.

Changes in cortical thickness and volume after cranial radiation treatment: A systematic review

Cognitive decline has a clear impact on quality of life in patients who have received cranial radiation treatment. The pathophysiological process is most likely multifactorial, with a possible role for decreased cortical thickness and volume. As radiotherapy treatment systems are becoming more sophisticated, precise sparing of vulnerable regions and tissue is possible. This allows radiation oncologists to make treatment more patient-tailored. A systematic search was performed to collect and review all available evidence regarding the effect of cranial radiation treatment on cortical thickness and volume. We searched the Pubmed, Embase and Cochrane databases, with an additional reference check in the Scopus database. Studies that examined cortical changes on MRI within patients as well as between treated and non-treated patients were included. The quality of the studies was assessed with a checklist specially designed for this review. No meta-analysis was performed due to the lack of randomised trials. Out of 1915 publications twenty-one papers were selected, of which fifteen observed cortical changes after radiation therapy. Two papers reported radiation-dependent decrease in cortical thickness within patients one year after radiation treatment, suggesting a clear relation between the two. However, study quality was considered mostly suboptimal, and there was great inhomogeneity between the included studies. This means that, although there has been increasing interest in the effects of radiation treatment on cortex morphology, no reliable conclusion can be drawn based on the currently available evidence. This calls for more research, preferably with a sufficiently large patient population, and adequate methodology.